Executive Briefings

Transvoyant Announces Predictive Tool for Supply Chain Risk

By: TransVoyant 03.29.2017

TransVoyant has announced its new product TransVoyant Precise Predictive Risk (P2R), a machine learning-based risk management and prediction tool that the software company says enables organizations to monitor, analyze and remediate risks to physical facilities, inventory in motion and in storage, human capital, competitors and extended trading partners around the world.

According to a 2013 research report published jointly by MIT and PwC, more than 69 percent of the 209 global enterprises surveyed experienced a supply chain disruption that resulted in a 3-percent or higher increase in total supply chain costs. For the average Fortune 500 company, that equates to $73m in incremental costs annually. Meanwhile, a 2014 survey of supply chain executives conducted by the Global Supply Chain Institute found that “many supply chain execs have done very little to formally manage supply chain risks.”

“As global supply chains have become more interdependent, distributed and complex, risk managers have struggled to keep track of their growing list of living assets and to identify and mitigate their risk exposure,” said TransVoyant CEO Dennis Groseclose. “Doing so requires risk managers to be nearly everywhere and to see nearly everything in real time and accurately peer into the future. By tapping into massive real-time big data streams that we collect every day from Internet of Things (IoT) devices around the world, and applying machine learning algorithms and behavior modeling, we not only enable organizations to see a broad range of risks unfolding in the now, but also to predict and avoid risks in the future.”

P2R triggers alerts to users when a disruptive event occurs or is imminent, and enables them to initiate actions. These actions include tasking airborne imagery, directing personnel to perform on-site inspections and assessments, assigning resources to fortify, protect and extract resources, and evaluating and initiating alternative scenarios via integration to supply chain planning and execution systems.

According to a 2013 research report published jointly by MIT and PwC, more than 69 percent of the 209 global enterprises surveyed experienced a supply chain disruption that resulted in a 3-percent or higher increase in total supply chain costs. For the average Fortune 500 company, that equates to $73m in incremental costs annually. Meanwhile, a 2014 survey of supply chain executives conducted by the Global Supply Chain Institute found that “many supply chain execs have done very little to formally manage supply chain risks.”

“As global supply chains have become more interdependent, distributed and complex, risk managers have struggled to keep track of their growing list of living assets and to identify and mitigate their risk exposure,” said TransVoyant CEO Dennis Groseclose. “Doing so requires risk managers to be nearly everywhere and to see nearly everything in real time and accurately peer into the future. By tapping into massive real-time big data streams that we collect every day from Internet of Things (IoT) devices around the world, and applying machine learning algorithms and behavior modeling, we not only enable organizations to see a broad range of risks unfolding in the now, but also to predict and avoid risks in the future.”

P2R triggers alerts to users when a disruptive event occurs or is imminent, and enables them to initiate actions. These actions include tasking airborne imagery, directing personnel to perform on-site inspections and assessments, assigning resources to fortify, protect and extract resources, and evaluating and initiating alternative scenarios via integration to supply chain planning and execution systems.